Triple
T12001487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Nene |
E285672
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | River Ise |
E826737
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: River Ise | Statement: [River Nene, hasTributary, River Ise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: River Ise Context triple: [River Nene, hasTributary, River Ise]
-
A.
River Ise
chosen
River Ise is a small river in Northamptonshire, England, that flows through the town of Kettering before joining the River Nene.
-
B.
Ise River
The Ise River is a tributary watercourse in Lower Saxony, Germany, that feeds into the Aller River within the Weser river basin.
-
C.
Yamatogawa
Yamatogawa is the romanized name of the Yamato River, a significant waterway in the Kansai region of Japan.
-
D.
Mukogawa River
The Mukogawa River is a prominent river in Japan’s Hyōgo Prefecture that flows through cities such as Nishinomiya before emptying into Osaka Bay.
-
E.
Furan River
The Furan River is a watercourse in eastern France that flows through the Loire department and the city of Saint-Étienne before joining the Ain River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c36b248190b446b17def94885b |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd646ee860819083277b15aaf510fd |
completed | May 8, 2026, 4:19 a.m. |
Created at: April 8, 2026, 9:46 p.m.